920112
48.9%
51.1%
Nov 30,'25
Geographic distribution of blood donors by ZIP code across the United States The map uses color shading to represent different ranges of donor counts: Dark blue: 1–5 donors Light green: 5–20 donors Yellow: 20–50 donors Orange: 50–100 donors Red: 100–1000 donors High-density donor areas (red and orange) are concentrated in parts of the Southeastern U.S., including Florida, Georgia, and Alabama, as well as the Midwest and Mid-Atlantic regions. Moderate donor density (yellow and green) appears across much of the eastern half of the country, while the western states show sparse donor distribution, with small clusters in California, Washington, and Colorado. Large areas in the Mountain West and rural regions have very low donor counts (blue).
Top Map: Red Cross donor counts in the U.S. aggregated across March, August, and November 2025. The highest concentrations in urban counties of the Midwest, Southeast, and parts of California and Texas. Sparse donor representation is observed in rural western regions. Donor density is strongly clustered in metropolitan areas, suggesting reliance on urban populations for blood supply. Bottom Map: Shows county-level prevalence of diabetes among blood donors aged ≥16 years, grouped into quintiles. Elevated rates in the Southeast and parts of Texas, while lower prevalence is seen in the Midwest and Mountain West. Diabetes prevalence among donors shows a geographic pattern similar to national trends, with the Southeast exhibiting the highest burden. Regions with high donor counts do not always correspond to diabetes prevalence, indicating potential challenges for donor health screening in high-prevalence areas.
Glycemic status distribution by age group and race/ethnicity among blood donors. The proportion of donors with diabetes and prediabetes increases markedly with age, while normal glycemic status declines. Among donors aged ≥55 years, diabetes prevalence reaches 7–15%, and prediabetes exceeds 40% in some racial groups. Younger donors (<29 years) show minimal diabetes (<1%) and high normal glycemic status (>90%). Racial differences are evident, with Hispanic and NH Asian/Other groups showing higher diabetes prevalence in older age categories.
Boxplots for A1c% by age-group are compared between female and male donors.
Median values are labeled for each.
For each age-group, males have higher median value than females.
Boxplots for A1c% by age-group are compared between asian, black, hispanic, and white donors.
Median values are labeled for each.
For each age-group, black donors have higher median value than others.
Blood donors exhibit substantially lower prevalence of diabetes and prediabetes compared to national estimates, particularly in older age groups. Among donors aged ≥55 years, diabetes prevalence is 7.4% versus 17.9% in NHANES, and normal glycemic status remains higher (67.1% vs 47.4%). These findings reflect a healthier metabolic profile among donors relative to the general population.
Interactive map showing ZIP code-level blood donor counts and diabetes prevalence. The left panel provides sliders to filter ZIP codes by diabetes prevalence (%) and donor count. The map displays ZIP codes as circles, with size and color indicating donor density and diabetes burden. High-density clusters are concentrated in metropolitan areas of the Midwest, Northeast, and Southeast, supporting targeted screening and recruitment strategies.
This visualization enables identification of ZIP codes with both high donor counts and high diabetes burden, supporting targeted screening and recruitment strategies.
Characteristic | normal | hypoglycemia | prediabetes | diabetes |
|---|---|---|---|---|
gender, n (%) | ||||
F | 374,535 (83%) | 32 (<0.1%) | 62,073 (14%) | 13,589 (3.0%) |
M | 353,796 (75%) | 70 (<0.1%) | 87,106 (19%) | 28,911 (6.2%) |
race/ethnicity, n (%) | ||||
Hispanic Origin | 38,925 (81%) | 6 (<0.1%) | 6,764 (14%) | 2,119 (4.4%) |
NH Asian/other | 47,431 (78%) | 5 (<0.1%) | 10,636 (17%) | 2,865 (4.7%) |
NH Black | 23,252 (66%) | 4 (<0.1%) | 9,118 (26%) | 2,616 (7.5%) |
NH White | 618,723 (80%) | 87 (<0.1%) | 122,661 (16%) | 34,900 (4.5%) |
age, Median (Q1, Q3) | 49 (34, 63) | 46 (33, 60) | 64 (55, 70) | 64 (55, 70) |
age group, n (%) | ||||
-29 | 148,483 (97%) | 24 (<0.1%) | 3,798 (2.5%) | 805 (0.5%) |
30-54 | 284,824 (87%) | 44 (<0.1%) | 33,357 (10%) | 9,040 (2.8%) |
55- | 295,024 (67%) | 34 (<0.1%) | 112,024 (25%) | 32,655 (7.4%) |
median household income, Median (Q1, Q3) | 58,463 (46,148, 76,074) | 60,066 (47,594, 78,902) | 56,395 (45,430, 72,813) | 54,143 (44,070, 69,257) |
Donor characteristics | Mar'25, N=3761471 | Aug'25, N=3007151 | Nov'25, N=2432501 |
|---|---|---|---|
A1c% (average, 95%CI) | 5.30 (5.10, 5.50) | 5.40 (5.20, 5.60) | 5.30 (5.10, 5.60) |
A1C_category | |||
normal | 307,486 (82%) | 226,992 (75%) | 193,853 (80%) |
hypoglycemia | 43 (<0.1%) | 31 (<0.1%) | 28 (<0.1%) |
prediabetes | 51,727 (14%) | 58,288 (19%) | 39,164 (16%) |
diabetes | 16,891 (4.5%) | 15,404 (5.1%) | 10,205 (4.2%) |
gender | |||
F | 182,685 (49%) | 146,864 (49%) | 120,680 (50%) |
M | 193,462 (51%) | 153,851 (51%) | 122,570 (50%) |
Race | |||
Hispanic Origin | 18,885 (5.0%) | 14,319 (4.8%) | 14,610 (6.0%) |
NH Asian/other | 22,537 (6.0%) | 20,095 (6.7%) | 18,305 (7.5%) |
NH Black | 13,733 (3.7%) | 10,430 (3.5%) | 10,827 (4.5%) |
NH White | 320,992 (85%) | 255,871 (85%) | 199,508 (82%) |
Age | 54 (37, 66) | 55 (41, 66) | 49 (32, 63) |
Age Group | |||
-29 | 65,258 (17%) | 33,570 (11%) | 54,282 (22%) |
30-54 | 126,470 (34%) | 112,212 (37%) | 88,583 (36%) |
55- | 184,419 (49%) | 154,933 (52%) | 100,385 (41%) |
First-Time Donor | 49,852 (13%) | 35,115 (12%) | 47,596 (20%) |
BMI group | |||
70,865 (19%) | 50,391 (17%) | 28,735 (12%) | |
morbid obestiy | 35,305 (9.4%) | 30,472 (10%) | 24,438 (10%) |
normal | 92,562 (25%) | 70,165 (23%) | 67,232 (28%) |
obese | 61,751 (16%) | 52,496 (17%) | 41,953 (17%) |
overweight | 114,905 (31%) | 96,772 (32%) | 80,288 (33%) |
underweight | 758 (0.2%) | 416 (0.1%) | 583 (0.2%) |
BMI | 27.4 (24.2, 31.2) | 27.5 (24.4, 31.5) | 27.3 (24.1, 31.1) |
1Median (Q1, Q3); n (%) | |||
| Characteristic |
Mar’25
|
Aug’25
|
Nov’25
|
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| normal N = 307,4861 |
hypoglycemia N = 431 |
prediabetes N = 51,7271 |
diabetes N = 16,8911 |
normal N = 226,9921 |
hypoglycemia N = 311 |
prediabetes N = 58,2881 |
diabetes N = 15,4041 |
normal N = 193,8531 |
hypoglycemia N = 281 |
prediabetes N = 39,1641 |
diabetes N = 10,2051 |
|
| A1c% | 5.20 (5.00, 5.40) | NA (NA, NA) | 5.80 (5.70, 6.00) | 7.10 (6.70, 7.90) | 5.30 (5.10, 5.40) | NA (NA, NA) | 5.80 (5.70, 6.00) | 7.10 (6.70, 7.80) | 5.20 (5.10, 5.40) | NA (NA, NA) | 5.80 (5.70, 6.00) | 7.10 (6.70, 7.80) |
| Gender | ||||||||||||
| F | 156,246 (86%) | 14 (<0.1%) | 21,153 (12%) | 5,272 (2.9%) | 117,288 (80%) | 8 (<0.1%) | 24,523 (17%) | 5,045 (3.4%) | 101,001 (84%) | 10 (<0.1%) | 16,397 (14%) | 3,272 (2.7%) |
| M | 151,240 (78%) | 29 (<0.1%) | 30,574 (16%) | 11,619 (6.0%) | 109,704 (71%) | 23 (<0.1%) | 33,765 (22%) | 10,359 (6.7%) | 92,852 (76%) | 18 (<0.1%) | 22,767 (19%) | 6,933 (5.7%) |
| Race | ||||||||||||
| Hispanic Origin | 15,793 (84%) | 1 (<0.1%) | 2,310 (12%) | 781 (4.1%) | 11,086 (77%) | 2 (<0.1%) | 2,448 (17%) | 783 (5.5%) | 12,046 (82%) | 3 (<0.1%) | 2,006 (14%) | 555 (3.8%) |
| NH Asian/other | 18,133 (80%) | 2 (<0.1%) | 3,415 (15%) | 987 (4.4%) | 14,837 (74%) | 2 (<0.1%) | 4,147 (21%) | 1,109 (5.5%) | 14,461 (79%) | 1 (<0.1%) | 3,074 (17%) | 769 (4.2%) |
| NH Black | 9,597 (70%) | 1 (<0.1%) | 3,157 (23%) | 978 (7.1%) | 6,019 (58%) | 1 (<0.1%) | 3,423 (33%) | 987 (9.5%) | 7,636 (71%) | 2 (<0.1%) | 2,538 (23%) | 651 (6.0%) |
| NH White | 263,963 (82%) | 39 (<0.1%) | 42,845 (13%) | 14,145 (4.4%) | 195,050 (76%) | 26 (<0.1%) | 48,270 (19%) | 12,525 (4.9%) | 159,710 (80%) | 22 (<0.1%) | 31,546 (16%) | 8,230 (4.1%) |
| Age | 50 (34, 64) | 47 (38, 64) | 64 (56, 71) | 64 (56, 71) | 51 (37, 64) | 46 (35, 63) | 64 (55, 70) | 64 (56, 71) | 45 (28, 60) | 38 (21, 60) | 62 (52, 69) | 63 (54, 70) |
| Age Group | ||||||||||||
| -29 | 63,835 (98%) | 9 (<0.1%) | 1,071 (1.6%) | 343 (0.5%) | 32,198 (96%) | 4 (<0.1%) | 1,161 (3.5%) | 207 (0.6%) | 52,450 (97%) | 11 (<0.1%) | 1,566 (2.9%) | 255 (0.5%) |
| 30-54 | 112,867 (89%) | 17 (<0.1%) | 10,268 (8.1%) | 3,318 (2.6%) | 95,893 (85%) | 18 (<0.1%) | 13,035 (12%) | 3,266 (2.9%) | 76,064 (86%) | 9 (<0.1%) | 10,054 (11%) | 2,456 (2.8%) |
| 55- | 130,784 (71%) | 17 (<0.1%) | 40,388 (22%) | 13,230 (7.2%) | 98,901 (64%) | 9 (<0.1%) | 44,092 (28%) | 11,931 (7.7%) | 65,339 (65%) | 8 (<0.1%) | 27,544 (27%) | 7,494 (7.5%) |
| First-Time Donor | 45,741 (92%) | 5 (<0.1%) | 2,992 (6.0%) | 1,114 (2.2%) | 29,305 (83%) | 6 (<0.1%) | 4,483 (13%) | 1,321 (3.8%) | 42,734 (90%) | 7 (<0.1%) | 3,802 (8.0%) | 1,053 (2.2%) |
| BMI group | ||||||||||||
| 55,577 (78%) | 11 (<0.1%) | 11,258 (16%) | 4,019 (5.7%) | 36,579 (73%) | 4 (<0.1%) | 10,682 (21%) | 3,126 (6.2%) | 21,839 (76%) | 6 (<0.1%) | 5,278 (18%) | 1,612 (5.6%) | |
| morbid obestiy | 23,595 (67%) | 2 (<0.1%) | 8,290 (23%) | 3,418 (9.7%) | 18,119 (59%) | 2 (<0.1%) | 9,104 (30%) | 3,247 (11%) | 15,570 (64%) | 0 (0%) | 6,509 (27%) | 2,359 (9.7%) |
| normal | 85,946 (93%) | 7 (<0.1%) | 5,483 (5.9%) | 1,126 (1.2%) | 61,507 (88%) | 7 (<0.1%) | 7,507 (11%) | 1,144 (1.6%) | 61,172 (91%) | 10 (<0.1%) | 5,238 (7.8%) | 812 (1.2%) |
| obese | 45,858 (74%) | 11 (<0.1%) | 11,664 (19%) | 4,218 (6.8%) | 35,503 (68%) | 6 (<0.1%) | 13,092 (25%) | 3,895 (7.4%) | 30,091 (72%) | 2 (<0.1%) | 9,254 (22%) | 2,606 (6.2%) |
| overweight | 95,786 (83%) | 12 (<0.1%) | 15,004 (13%) | 4,103 (3.6%) | 74,903 (77%) | 12 (<0.1%) | 17,869 (18%) | 3,988 (4.1%) | 64,606 (80%) | 9 (<0.1%) | 12,863 (16%) | 2,810 (3.5%) |
| underweight | 723 (95%) | 0 (0%) | 28 (3.7%) | 7 (0.9%) | 379 (91%) | 0 (0%) | 33 (7.9%) | 4 (1.0%) | 555 (95%) | 1 (0.2%) | 21 (3.6%) | 6 (1.0%) |
| BMI | 26.6 (23.7, 30.4) | 27.2 (25.2, 31.3) | 29.9 (26.6, 33.9) | 31.2 (27.8, 35.3) | 27.0 (24.0, 30.5) | 27.5 (24.1, 31.3) | 29.5 (26.4, 33.5) | 31.0 (27.6, 35.3) | 26.6 (23.6, 30.3) | 24.9 (21.9, 28.7) | 29.5 (26.4, 33.5) | 31.0 (27.7, 35.4) |
| 1 Median (Q1, Q3); n (%) | ||||||||||||